CN115329919A

CN115329919A - Random additional point anti-counterfeiting method and device based on micro-point code

Info

Publication number: CN115329919A
Application number: CN202211219471.2A
Authority: CN
Inventors: 鞠翔; 贾元新; 苟佳洁; 匡扶; 孙可; 严维同
Original assignee: Beijing Microdot Science And Technology Co ltd
Current assignee: Beijing Microdot Science And Technology Co ltd; Microcode Liaoning Technology Co ltd
Priority date: 2022-10-08
Filing date: 2022-10-08
Publication date: 2022-11-11
Anticipated expiration: 2042-10-08
Also published as: CN115329919B

Abstract

The invention provides a random additional point anti-counterfeiting method and a random additional point anti-counterfeiting device based on a micro-point code, wherein the method comprises the following steps: generating a dot matrix code image by using any original code value based on the code system of the micro-dot code; processing the original code value by using a dynamic encryption algorithm and a dynamic encryption parameter corresponding to the original code value to obtain an original graph anti-counterfeiting feature embedded password; determining code point row numbers, code point column numbers, embedding directions, embedding offsets and the number of pixels added outwards relative to the center of code points of a plurality of graph anti-counterfeiting characteristics of the embedded dot matrix code graph according to the original graph anti-counterfeiting characteristic embedded password and a graph anti-counterfeiting characteristic embedding algorithm; embedding a plurality of graphic anti-counterfeiting features in the dot matrix code graph to obtain a random additional dot graphic security code electronic document; and printing the random additional point graphic security code electronic document into a random additional point graphic security code real object identification so as to detect the random additional point graphic security code real object identification to be detected to judge authenticity.

Description

Random additional point anti-counterfeiting method and device based on micro-point code

Technical Field

The invention relates to the technical field of anti-counterfeiting, in particular to a random additional point anti-counterfeiting method and device based on a micro-point code.

Background

The most common two types of one-object-one-code anti-counterfeiting schemes currently prevail: the first type is digital verification based on two-dimensional codes and numbers, and the application defects are that the safety is poor: the two-dimensional code and the number which are visible on the printed matter are used as the ID of the article and can be counterfeited in batches at low cost, various pattern numbers can be copied after being visible due to the manufacturing source of the two-dimensional code, the hidden verification code corresponding to the ID usually needs a fragile coating process, can be checked only by uncovering and scraping after being purchased by a consumer, and can not effectively check the correctness of the ID and the verification code before being purchased under nondestructive verification; the second type is based on artificial or natural random detail characteristics during printing to acquire images after printing, and adopts an image uploading or downloading mode to extract and compare the image details during terminal user verification, so that although the defect that the first type cannot perform pre-purchase anti-counterfeiting verification on consumers is overcome, the second type has the defects that a production line of a production enterprise needs to be modified, special image acquisition analysis uploading software and hardware are erected, high-definition image details stored at the cloud end occupy a large amount of storage cost, and obvious flow and time are consumed when a user performs anti-counterfeiting detection. The two types of common problems are poor user experience, such as long time for searching the database for duplicate generated by a large number of unique codes, slow and high-definition image downloading of random unique codes in the database or long time for verifying authenticity by cloud comparison of local detection image uploading.

Disclosure of Invention

The embodiment of the invention aims to provide a random additional point anti-counterfeiting method and device based on a micro-point code, and the random additional point anti-counterfeiting method and device based on the micro-point code are more balanced in multiple aspects of comprehensive cost, inspection experience and anti-counterfeiting performance.

In order to achieve the above object, an embodiment of the present invention provides a random additional point anti-counterfeiting method based on a micro-point code, where the method includes: generating a dot matrix code image by using any original code value based on the code system of the micro-dot code; processing the original code value by using a dynamic encryption algorithm and a dynamic encryption parameter corresponding to the original code value to obtain an original graph anti-counterfeiting feature embedded password; determining code point row numbers, code point column numbers, embedding directions, embedding offsets and the number of outwards added pixels relative to the code point center of a plurality of pattern anti-counterfeiting features embedded in the dot matrix code pattern according to the original pattern anti-counterfeiting feature embedded password and a pattern anti-counterfeiting feature embedding algorithm; embedding the plurality of graphic anti-counterfeiting features into the dot matrix code image according to the code point row number, the code point column number, the embedding direction, the embedding offset and the number of the pixels added outwards from the center of the relative code point to obtain a random additional point graphic security code electronic document; storing a dynamic encryption parameter corresponding to the original code value, an original graph anti-counterfeiting feature fingerprint corresponding to the original code value and an N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch to a server, wherein the original graph anti-counterfeiting feature fingerprint is obtained by processing the random additional point graph security code electronic document by using the original graph anti-counterfeiting feature embedded password and a graph anti-counterfeiting feature extraction algorithm corresponding to the graph anti-counterfeiting feature embedded algorithm; and printing the random additional point pattern security code electronic document into a random additional point pattern security code real object identifier so as to detect the random additional point pattern security code real object identifier to be detected according to the dynamic encryption parameter corresponding to the original code value, the original pattern anti-counterfeiting feature fingerprint corresponding to the original code value and the N frames of anti-counterfeiting feature fingerprint authenticity judgment threshold values corresponding to the current printing batch so as to judge authenticity.

Preferably, the processing the original code value by using a dynamic encryption algorithm and a dynamic encryption parameter corresponding to the original code value to obtain an original graphic anti-counterfeiting feature embedded password comprises: based on a linear congruence method, executing n times of random number generation operation to obtain an original graph anti-counterfeiting feature embedded password prototype; intercepting and splitting the anti-counterfeiting feature of the original graph embedded password prototype into 5 character strings; respectively carrying out MD5 encryption on the 5 character strings to obtain 5 encrypted character strings; and respectively taking the front 4 bits or the rear 4 bits of the 5 encrypted character strings to generate 5 arrays with the length of 4, and combining the arrays to obtain the original graph anti-counterfeiting feature embedded password.

Preferably, determining the code dot row number, the code dot column number, the embedding direction, the embedding offset and the number of the pixels added outwards relative to the code dot center of the plurality of graphic anti-counterfeiting features embedded in the dot matrix code pattern according to the original graphic anti-counterfeiting feature embedded password and the graphic anti-counterfeiting feature embedded algorithm comprises: the 1 st bit to the 4 th bit of the original graph anti-counterfeiting feature embedded password is converted into a first digital array through ASCII coding; taking the first 4 or the last 4 numbers of the first digital array, setting the odd number in each number as 1 and the even number as 0, and generating a first binary number with 4 bits; converting the first binary digits into decimal digits to obtain code point row numbers of a plurality of graph anti-counterfeiting features embedded into the dot matrix code graph; the 5 th bit to the 8 th bit of the original graph anti-counterfeiting feature embedded password is converted into a second digital array through ASCII coding; taking the first 4 or the last 4 numbers of the second digital array, setting the odd number in each number as 1 and the even number as 0, and generating a second binary digit with 4 bits; converting the second binary digits into decimal digits to obtain code point column numbers of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code graph; converting the 9 th bit to the 12 th bit of the original graph anti-counterfeiting feature embedded password into a third digital array by ASCII coding; taking the first 4 or the last 4 numbers of the third digital array, setting the odd number in each number as 1 and the even number as 0, and generating a 4-bit third binary digit; converting the third binary digit into a decimal digit, dividing the decimal digit by 2, rounding, and adding 1 to obtain a first integer; determining the embedding directions of a plurality of graphic anti-counterfeiting features embedded into the dot matrix code pattern according to the first integer; converting 13 th to 16 th bits of the original graph anti-counterfeiting feature embedded password into a fourth digital array through ASCII (American standard code for information interchange) coding; taking the first 4 or the last 4 numbers of the fourth digital array, setting the odd number in each number as 1 and the even number as 0, and generating a fourth binary digit with 4 bits; converting the fourth binary digit into a decimal digit, dividing the decimal digit by 4, and rounding down to obtain a second integer; determining the embedded offset of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code pattern according to the second integer; the 17 th bit to the 20 th bit of the original graph anti-counterfeiting feature embedded password is converted into a fifth digital array through ASCII coding; taking the first 4 or the last 4 numbers of the fifth digital array, setting the odd number in each number as 1 and the even number as 0, and generating a fifth binary digit with 4 bits; converting the fifth binary digit into a decimal digit, dividing the decimal digit by 2, rounding, and adding 1 to obtain a third integer; and determining the number of the pixels added outwards relative to the code point center of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code graph according to the third integer.

Preferably, the detecting the physical identifier of the random additional dot pattern security code to be detected to judge the authenticity according to the dynamic encryption parameter corresponding to the original code value, the original pattern security feature fingerprint corresponding to the original code value and the N frames of security feature fingerprint authenticity judgment threshold corresponding to the current printing batch comprises: extracting a code value to be detected of the random additional dot pattern security code real object identifier to be detected; when the extraction is unsuccessful within the preset time or the extracted code value to be detected is not stored in the server, a counterfeit product is prompted; when the extracted code value to be detected is stored in the server, acquiring a dynamic encryption parameter corresponding to the code value to be detected, an original graph anti-counterfeiting feature fingerprint corresponding to the code value to be detected and an N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch from the server; processing the code value to be detected by using the dynamic encryption algorithm and the dynamic encryption parameter corresponding to the code value to be detected to obtain an embedded password of the anti-counterfeiting feature of the graph to be detected; according to the graph anti-counterfeiting feature embedding password to be detected and the graph anti-counterfeiting feature extraction algorithm, obtaining a graph anti-counterfeiting feature fingerprint to be detected of the randomly attached dot-graph security code physical identification to be detected; comparing the graph anti-counterfeiting characteristic fingerprint to be detected with an original graph anti-counterfeiting characteristic fingerprint corresponding to the code value to be detected, and calculating the matching rate of two character strings in the same character set encoding mode to obtain a single-frame passing result; when the number of the single-frame passing results is accumulated to N, calculating a multi-frame passing rate statistic value; when the multi-frame passing rate statistic value is smaller than the authenticity judgment threshold value of the N frames of anti-counterfeiting feature fingerprints corresponding to the current printing batch, prompting a counterfeit product; and prompting the genuine product when the multi-frame passing rate statistic value is greater than or equal to the authenticity judgment threshold value of the N frames of anti-counterfeiting feature fingerprints corresponding to the current printing batch.

Preferably, the method further comprises: acquiring M graphic anti-counterfeiting characteristic fingerprints of random additional dot graphic security code real object identifications corresponding to the same original code value; comparing the graph anti-counterfeiting feature fingerprints of the random additional point graph security code real object identification corresponding to M identical original code values with the original graph anti-counterfeiting feature fingerprints corresponding to the original code values to obtain an average value of M single-frame matching rates; and when the average value is smaller than the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch, updating the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch as the average value to the server.

Preferably, the step of obtaining the fingerprint of the to-be-detected pattern anti-counterfeiting feature of the to-be-detected randomly-added dot pattern security code physical identifier according to the to-be-detected pattern anti-counterfeiting feature embedded password and the pattern anti-counterfeiting feature extraction algorithm comprises: comparing the graph anti-counterfeiting feature embedding password to be detected with an original graph anti-counterfeiting feature embedding password corresponding to the code value to be detected, and writing a comparison result into the graph anti-counterfeiting feature fingerprint to be detected; verifying the contour length of the graphic anti-counterfeiting feature of the random additional point graphic security code real object identifier to be detected, and obtaining a first verification result; verifying the area hit of the graph anti-counterfeiting feature of the random additional point graph security code physical identification to be detected, and obtaining a second verification result; verifying the corner points of the graph anti-counterfeiting characteristics of the random additional point graph security code real object identifier to be detected, and obtaining a third verification result; obtaining a comparison result according to the first verification result, the second verification result, the third verification result and the respective threshold values, and writing the comparison result into the anti-counterfeiting characteristic fingerprint of the graph to be detected; and outputting the anti-counterfeiting characteristic fingerprint of the graph to be detected.

Preferably, the code value can be a character string encoded by any character, when the code value of the micro-point code is converted into a binary system, an obvious gap larger than or equal to 1 data position exists between data, the random additional point pattern safety code object mark manufactured by the micro-point code has at least 90% robustness in a 20mm-20mm area, can be decoded in a contaminated area to any residual 3mm-3mm complete area, and can be read under an interference pattern except linear, nodular and special-shaped code points.

The embodiment of the invention also provides a random additional point anti-counterfeiting device based on the micro-point code, which comprises: the system comprises a code map generating module, a password acquiring module, a document acquiring module, a parameter storage module and an identification processing module, wherein the code map generating module is used for generating a dot matrix code map by using any original code value based on a code system of a micro-point code; the password acquisition module is used for processing the original code value by using a dynamic encryption algorithm and a dynamic encryption parameter corresponding to the original code value to obtain an original graph anti-counterfeiting feature embedded password; the document acquisition module is used for: determining code point row numbers, code point column numbers, embedding directions, embedding offsets and the number of outwards added pixels relative to the code point center of a plurality of pattern anti-counterfeiting features embedded in the dot matrix code pattern according to the original pattern anti-counterfeiting feature embedded password and a pattern anti-counterfeiting feature embedding algorithm; embedding the plurality of graphic anti-counterfeiting features into the dot matrix code image according to the code point row number, the code point column number, the embedding direction, the embedding offset and the number of the pixels added outwards from the center of the relative code point to obtain a random additional point graphic security code electronic document; the parameter storage module is used for storing a dynamic encryption parameter corresponding to the original code value, an original graph anti-counterfeiting feature fingerprint corresponding to the original code value and an N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch to a server, wherein the original graph anti-counterfeiting feature fingerprint is obtained by processing the random additional point graph security code electronic document by using the original graph anti-counterfeiting feature embedded password and a graph anti-counterfeiting feature extraction algorithm corresponding to the graph anti-counterfeiting feature embedded algorithm; the mark processing module is used for printing the random additional point pattern security code electronic document into a random additional point pattern security code real object mark so as to detect the random additional point pattern security code real object mark to be detected according to the dynamic encryption parameter corresponding to the original code value, the original pattern anti-counterfeiting feature fingerprint corresponding to the original code value and the N frames of anti-counterfeiting feature fingerprint authenticity judgment threshold values corresponding to the current printing batch so as to judge authenticity.

Preferably, the password obtaining module is configured to: based on a linear congruence method, executing n times of random number generation operation to obtain an original graph anti-counterfeiting feature embedded password prototype; intercepting and splitting the anti-counterfeiting feature of the original graph embedded password prototype into 5 character strings; respectively carrying out MD5 encryption on the 5 character strings to obtain 5 encrypted character strings; and respectively taking the front 4 bits or the rear 4 bits of the 5 encrypted character strings to generate 5 arrays with the length of 4, and combining the arrays to obtain the original graph anti-counterfeiting feature embedded password.

Preferably, the document acquisition module is configured to: the 1 st bit to the 4 th bit of the original graph anti-counterfeiting feature embedded password is converted into a first digital array through ASCII coding; taking the first 4 or the last 4 numbers of the first digital array, setting the odd number in each number as 1 and the even number as 0, and generating a first binary number with 4 bits; converting the first binary digits into decimal digits to obtain code point row numbers of a plurality of graph anti-counterfeiting features embedded into the dot matrix code graph; the 5 th bit to the 8 th bit of the original graph anti-counterfeiting feature embedded password is converted into a second digital array through ASCII coding; taking the first 4 or the last 4 numbers of the second digital array, setting the odd number in each number as 1 and the even number as 0, and generating a second binary digit with 4 bits; converting the second binary digits into decimal digits to obtain code point column numbers of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code graph; converting the 9 th bit to the 12 th bit of the original graph anti-counterfeiting feature embedded password into a third digital array by ASCII coding; taking the first 4 or the last 4 numbers of the third digital array, setting the odd number in each number as 1 and the even number as 0, and generating a 4-bit third binary digit; converting the third binary digit into a decimal digit, dividing the decimal digit by 2, rounding down, and adding 1 to obtain a first integer; determining the embedding directions of a plurality of graphic anti-counterfeiting features embedded into the dot matrix code pattern according to the first integer; converting 13 th to 16 th bits of the original graph anti-counterfeiting feature embedded password into a fourth digital array through ASCII (American standard code for information interchange) coding; taking the first 4 or the last 4 numbers of the fourth digital array, setting the odd number in each number as 1 and the even number as 0, and generating a fourth binary digit with 4 bits; converting the fourth binary digit into a decimal digit, dividing the decimal digit by 4, and rounding down to obtain a second integer; determining the embedded offset of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code pattern according to the second integer; the 17 th bit to the 20 th bit of the original graph anti-counterfeiting feature embedded password is converted into a fifth digital array through ASCII coding; taking the first 4 or the last 4 numbers of the fifth digital array, setting the odd number in each number as 1 and the even number as 0, and generating a fifth binary digit with 4 bits; converting the fifth binary digit into a decimal digit, dividing the decimal digit by 2, rounding, and adding 1 to obtain a third integer; and determining the number of the pixels added outwards relative to the code point center of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code graph according to the third integer.

Preferably, the identification processing module is configured to: extracting a code value to be detected of the random additional dot pattern security code real object identifier to be detected; when the extraction is unsuccessful within the preset time or the extracted code value to be detected is not stored in the server, a counterfeit product is prompted; when the extracted code value to be detected is stored in the server, acquiring a dynamic encryption parameter corresponding to the code value to be detected, an original graph anti-counterfeiting feature fingerprint corresponding to the code value to be detected and an N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch from the server; processing the code value to be detected by using the dynamic encryption algorithm and the dynamic encryption parameter corresponding to the code value to be detected to obtain an embedded password of the anti-counterfeiting feature of the graph to be detected; according to the graph anti-counterfeiting feature embedding password to be detected and the graph anti-counterfeiting feature extraction algorithm, obtaining a graph anti-counterfeiting feature fingerprint to be detected of the randomly attached dot-graph security code physical identification to be detected; comparing the graph anti-counterfeiting characteristic fingerprint to be detected with an original graph anti-counterfeiting characteristic fingerprint corresponding to the code value to be detected, and calculating the matching rate of two character strings in the same character set encoding mode to obtain a single-frame passing result; when the number of the single-frame passing results is accumulated to N, calculating a multi-frame passing rate statistic value; when the multi-frame throughput rate statistic value is smaller than the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch, prompting a counterfeit product; and prompting the genuine product when the multi-frame passing rate statistic value is greater than or equal to the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch.

Preferably, the apparatus further comprises a parameter adjusting module for: acquiring graph anti-counterfeiting characteristic fingerprints of M random additional point graph security code real object identifications corresponding to the same original code value; comparing the graph anti-counterfeiting feature fingerprints of the random additional point graph security code real object identification corresponding to M identical original code values with the original graph anti-counterfeiting feature fingerprints corresponding to the original code values to obtain an average value of M single-frame matching rates; and when the average value is smaller than the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch, updating the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch as the average value to the server.

Preferably, the identification processing module is configured to: comparing the graph anti-counterfeiting feature embedding password to be detected with an original graph anti-counterfeiting feature embedding password corresponding to the code value to be detected, and writing a comparison result into the graph anti-counterfeiting feature fingerprint to be detected; verifying the contour length of the graphic anti-counterfeiting feature of the random additional point graphic security code real object identifier to be detected, and obtaining a first verification result; verifying the area hit of the graph anti-counterfeiting feature of the random additional point graph security code physical identification to be detected, and obtaining a second verification result; verifying the corner points of the graph anti-counterfeiting characteristics of the random additional point graph security code real object identifier to be detected, and obtaining a third verification result; obtaining comparison results according to the first verification result, the second verification result, the third verification result and the respective threshold values, and writing the comparison results into the anti-counterfeiting characteristic fingerprint of the graph to be detected; and outputting the anti-counterfeiting characteristic fingerprint of the graph to be detected.

Through the technical scheme, the security is improved by selecting the non-open-source micro-point code system to replace the traditional open-source code system, so that a counterfeiter is prevented from directly acquiring code values through software of an open-source two-dimensional code decoding algorithm and generating the code values to forge single codes, and even guessing numbers according to an attempt observation rule to forge a large number of one-object one-code batch forgings; because a non-open source code system is selected, continuous numbers can be directly used as code value IDs, and the feedback time of system inspection is greatly shortened; the technology of embedding and extracting the anti-counterfeiting characteristic of the graph is added to the traditional digital verification technology, and the original non-anti-copying printed matter has the anti-copying effect on the basis of the micro-point code graph; the dynamic encryption technology is used for establishing the relationship between the code value ID and the anti-counterfeiting feature embedded password, and the code value of each code cannot be effectively obtained even if an attacker decrypts the program through decompilation due to the dynamic property, so that the technical safety of the anti-counterfeiting scheme is greatly improved; other colors are not needed, and the anti-counterfeiting feature embedding support of the industrialized high-speed variable single black code spraying process is increased.

Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.

Drawings

The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:

FIG. 1 is a flowchart of a random append point anti-counterfeiting method based on a micro-point code according to an embodiment of the present invention;

FIG. 2 is a flowchart of a method for determining an embedded password of an original graphical anti-counterfeiting feature according to an embodiment of the present invention;

FIG. 3 is a flowchart of a method for determining a plurality of anti-counterfeiting features embedded in the dot code pattern according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of an original graphical security feature embedded password distribution provided by an embodiment of the invention;

FIG. 5 is a schematic illustration of the direction of embedding of a plurality of graphical security features provided by one embodiment of the present invention;

FIG. 6 is a graphical illustration of an embedded offset for a plurality of graphical security features provided in accordance with an embodiment of the present invention;

FIG. 7 is a graphical representation of the number of outwardly added pixels relative to the center of a codepoint for a plurality of graphical security features provided in accordance with one embodiment of the present invention;

FIG. 8A is a diagram of a dot matrix code pattern according to an embodiment of the present invention;

FIG. 8B is a diagram of an electronic document with a random dot pattern security code according to an embodiment of the present invention;

fig. 9 is a flowchart of a method for detecting a physical identifier of a random dot pattern security code to be detected according to an embodiment of the present invention;

FIG. 10 is a flowchart of a method for determining a fingerprint of a security feature of a graphic to be detected according to an embodiment of the present invention;

FIG. 11 is a flowchart of a method for dynamically adjusting a decision threshold according to an embodiment of the invention;

fig. 12 is a schematic structural diagram of a random additional point anti-counterfeiting device based on a micro-point code according to an embodiment of the present invention.

Detailed Description

The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.

Fig. 1 is a flowchart of a random additional point anti-counterfeiting method based on a micro-point code according to an embodiment of the present invention. As shown in fig. 1, the method includes:

s101, based on the code system of the micro-point codes, generating a dot matrix code image by using any original code value;

the micro dot code is a sparse dot code with high robustness, and is an encoding algorithm and a decoding algorithm which are not open sources, the code pattern can not be read by decoding algorithms of other open source codes, compared with a traditional dense two-dimensional code in which code values are converted into binary systems 1 and 0 which are respectively arranged in a deep code dot form and a shallow code dot form, obvious gaps of more than or equal to 1 data position exist between data which are converted into binary systems by the micro dot code, and the code value can be a character string of any character code.

The physical mark of the random additional point graph security code manufactured by using the micro point code supports that more than 90% robustness is achieved in 20mm x 20mm, contamination is supported until any residual 3mm x 3mm complete area can still be decoded, 15% fault tolerance is achieved in the 3mm x 3mm minimum readable area, and the mark can still be read under interference graphs except linear, nodular and special-shaped code points. The lattice code system meeting the robustness condition provides powerful guarantee for embedding anti-counterfeiting features with enough quantity, area and position independence.

The code value of the traditional digital code check must ensure random discreteness to prevent a counterfeiter from decoding randomly, guess the law and try out the source code system for encoding for free to easily forge. And this embodiment can use continuous digit as the code value, greatly promotes the efficiency and the anti-guess number that the code value generated. Meanwhile, the micro dot codes can achieve the effect of retaining the aesthetic property of the almost invisible anti-counterfeiting mark outside 15cm and the aesthetic feeling of the brand.

In the embodiment, a plurality of micro-point codes which are disclosed or not disclosed at present are selected as codes to be processed for anti-counterfeiting. The purpose of selecting the micro-point code system is as follows: can generate the two-dimensional code image printing of arbitrary size (generally more than 3 mm) according to anti-fake detection demand on stock surface, compare that traditional intensive two-dimensional code needs 8 mm's anti-fake detection size less influence the packing beautifully, have more anti-fake disguise at least. Compared with traditional high-density two-dimensional Code images such as Data Matrix, maxiCode, aztec, QR Code, PDF417, vericode, ultracode, code 49 and Code 16K, the micro-point Code image is visually represented by more light-colored lattices and no obvious boundary which can be distinguished by human eyes.

The embodiment of the present invention is described only for any original code value, but those skilled in the art should understand that other different original code values exist for the anti-counterfeiting of different articles due to the principle of one object and one code. For other original code values, the processing of the embodiment of the present invention may also be used in the same way, and is not described herein again.

Step S102, processing the original code value by using a dynamic encryption algorithm and a dynamic encryption parameter corresponding to the original code value to obtain an original graph anti-counterfeiting feature embedded password;

wherein, as shown in fig. 2, the following steps S201-204 of the present invention provide an embodiment of obtaining the original graphical security feature embedded password, which is preferable for the embedded graphical security feature of the present invention, but those skilled in the art should understand that the present invention is not limited thereto.

Step S201, based on a linear congruence method, executing n times of random number generation operation to obtain an original graph anti-counterfeiting feature embedded password prototype;

wherein n is the dynamic encryption parameter corresponding to the original code value.

Step S202, intercepting and splitting the anti-counterfeiting feature of the original graph embedded password prototype into 5 character strings;

step S203, respectively carrying out MD5 encryption on the 5 character strings to obtain 5 encrypted character strings;

and S204, respectively taking the front 4 bits or the back 4 bits of the 5 encrypted character strings, generating 5 arrays with the length of 4, and combining the arrays to obtain the original graph anti-counterfeiting feature embedded password.

Therein, it is to be understood that the preferred original graphical security feature embedding password for the embedded graphical security feature of the present invention is a 20-digit string. The embodiment of the invention improves the anti-cracking performance of the technology through dynamic variability, and the corresponding verification improves the resistance of batch counterfeiting.

Step S103, determining code point row numbers, code point column numbers, embedding directions, embedding offsets and the number of pixels added outwards relative to the code point center of a plurality of graph anti-counterfeiting features embedded in the dot matrix code graph according to the original graph anti-counterfeiting feature embedded password and the graph anti-counterfeiting feature embedded algorithm;

as shown in fig. 3, step S103 includes steps S301 to S318, where as shown in fig. 4, the first 4 bits of the original graphical anti-counterfeiting feature embedded password determine the code dot row number of the multiple graphical anti-counterfeiting features embedded in the dot matrix code pattern; 5-8 bits determine code point serial numbers of a plurality of graphic anti-counterfeiting features embedded into the dot matrix code graph; 9-12 bits determine the embedding direction of a plurality of pattern anti-counterfeiting features embedded into the dot matrix code pattern; determining the embedded offset of a plurality of graphic anti-counterfeiting features embedded into the dot matrix code pattern by 13-16 bits; the 17-20 bits determine the number of the pixels which are added outwards relative to the code point center of the anti-counterfeiting features of the plurality of graphs embedded in the dot matrix code graph.

Steps S301 to S318 specifically include:

step S301, converting the 1 st to 4 th bits of the anti-counterfeiting feature embedded password of the original graph into a first digital array through ASCII coding;

step S302, taking the first 4 or the last 4 numbers of the first number array, setting the odd number in each number as 1 and the even number as 0, and generating a first binary number with 4 bits;

step S303, converting the first binary digits into decimal digits to obtain code point row numbers of a plurality of graph anti-counterfeiting features embedded into the dot matrix code graph;

wherein the plurality of graphical security features are embedded into all of the code points of the row.

Step S304, the 5 th to 8 th bits of the original graph anti-counterfeiting feature embedded password are converted into a second digital array through ASCII coding;

step S305, taking the first 4 or the last 4 numbers of the second digital array, setting the odd number in each number as 1 and the even number as 0, and generating a second binary digit with 4 bits;

step S306, converting the second binary digits into decimal digits to obtain code point sequence numbers of a plurality of graphic anti-counterfeiting features embedded into the dot matrix code image;

wherein a plurality of graphical security features are embedded into all of the code points of the column.

Step S307, converting the 9 th bit to the 12 th bit of the original graph anti-counterfeiting feature embedded password into a third digital array through ASCII coding;

step S308, taking the first 4 or the last 4 numbers of the third digital array, setting the odd number in each number as 1 and the even number as 0, and generating a 4-bit third binary digit;

step S309, converting the third binary digit into a decimal digit, dividing the decimal digit by 2, rounding down, and adding 1 to obtain a first integer;

step S310, determining the embedding directions of the anti-counterfeiting features of the multiple graphs embedded into the dot matrix code pattern according to the first integer;

as shown in FIG. 5, 1 is an integer less than or equal to 8, and each value corresponds to a direction. The number 1 is aligned right up and left, the number 2 is aligned right up and right, the number 3 is aligned right and left, the number 4 is aligned right and right, the number 5 is aligned right down and left, the number 6 is aligned right and right, the number 7 is aligned left and right, and the number 8 is aligned right and left.

Step S311, converting the 13 th bit to the 16 th bit of the original graph anti-counterfeiting feature embedded password into a fourth digital array through ASCII coding;

step S312, taking the first 4 or the last 4 numbers of the fourth digital array, setting the odd number in each digital array as 1, and setting the even number as 0, and generating a fourth binary digit with 4 bits;

step 313, converting the fourth binary digit into a decimal digit, dividing the decimal digit by 4, and rounding down to obtain a second integer;

step S314, determining the embedded offset of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code pattern according to the second integer;

as shown in FIG. 6, 0 is less than or equal to the second integer less than or equal to 3, each value corresponds to an offset, 0 represents an offset of 0,1 represents an offset of 1,2 represents an offset of 2,3 represents an offset of 3. Which ultimately determines the amount of embedded offset of the security feature points in the corresponding direction.

Step S315, the 17 th to 20 th bits of the original graph anti-counterfeiting feature embedded password are converted into a fifth digital array through ASCII coding;

step S316, taking the first 4 or the last 4 numbers of the fifth number array, setting the odd number in each number as 1, and setting the even number as 0, and generating a 4-bit fifth binary number;

step S317, converting the fifth binary digit into a decimal digit, dividing the decimal digit by 2, rounding down, and adding 1 to obtain a third integer;

and step S318, determining the number of the pixels which are added outwards relative to the code point center of the plurality of graphic anti-counterfeiting features embedded into the dot matrix code pattern according to the third integer.

As shown in FIG. 7, the third integer is greater than or equal to 1 and less than or equal to 8, each value corresponds to a number level of the added anti-counterfeiting features, and each level corresponds to the number of pixels added outward relative to the center of the image. Fig. 7 shows the anti-counterfeit feature points with 3 levels (third integer) added in the case that the offset is 3 in the right-left alignment direction of the code points.

The pattern anti-counterfeiting feature embedded in the embodiment of the invention is a pure black dot, and an effective anti-counterfeiting feature embedding mode is provided for a code spraying printing process which cannot embed a color dot.

Step S104, embedding the plurality of graphic anti-counterfeiting features into the dot matrix code image according to the code point row number, the code point column number, the embedding direction, the embedding offset and the number of the pixels added outwards relative to the code point center to obtain a random additional point graphic security code electronic document;

fig. 8B is a schematic diagram of an electronic document with a random dot pattern security code. The dot matrix code image is obtained by embedding the graphic anti-counterfeiting features in the step S103 on the basis of the dot matrix code image in fig. 8A, wherein the basis of the embedding of the graphic anti-counterfeiting features is that the row number of the code points is 2, the column number of the code points is 3, the dot adding direction is right-left-right alignment, the offset is 3, and the number is 6.

Step S105, storing a dynamic encryption parameter corresponding to the original code value, an original graph anti-counterfeiting feature fingerprint corresponding to the original code value and an N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch to a server, wherein the original graph anti-counterfeiting feature fingerprint is obtained by processing the random additional point graph security code electronic document by using the original graph anti-counterfeiting feature embedded password and a graph anti-counterfeiting feature extraction algorithm corresponding to the graph anti-counterfeiting feature embedded algorithm;

the authenticity judgment threshold value of the anti-counterfeiting feature fingerprint of N (N is more than or equal to 3 and less than or equal to 10) frames corresponding to the current printing batch can be uniformly preset according to subjective experience, and N can be adjusted according to the performance of the smart phone and the user experience expectation. And storing the dynamic encryption parameters corresponding to the original code values, the original pattern anti-counterfeiting characteristic fingerprints corresponding to the original code values and the N frames of anti-counterfeiting characteristic fingerprint authenticity judgment threshold values corresponding to the current printing batch into a server for later use when other random additional point pattern safety code real object identifications are detected. An example of the specific manner in which a fingerprint (e.g., an original graphical security feature fingerprint) may be obtained is set forth in detail below.

And S106, printing the random additional point pattern security code electronic document into a random additional point pattern security code real object identifier so as to detect the random additional point pattern security code real object identifier to be detected according to the dynamic encryption parameter corresponding to the original code value, the original pattern anti-counterfeiting feature fingerprint corresponding to the original code value and the N frames of anti-counterfeiting feature fingerprint authenticity judgment threshold values corresponding to the current printing batch so as to judge authenticity.

As shown in fig. 9, the detecting the physical identifier of the random dot pattern security code to be detected includes steps S901 to 909:

step S901, extracting a code value to be detected of the random additional dot pattern security code real object identifier to be detected;

the method comprises the steps of continuously obtaining an image of a random additional point pattern security code real object identifier to be detected by using a smart phone preview frame, trying to obtain a value of a to-be-detected code of the random additional point pattern security code real object identifier to be detected through a dot matrix code decoding algorithm, and continuously obtaining a next preview frame image if the value of the to-be-detected code cannot be obtained through decoding.

Step S902, when the extraction is unsuccessful within a preset time or the extracted code value to be detected is not stored in the server, a counterfeit is prompted;

wherein, preferably, if the decoding is unsuccessful for more than 15 seconds, the user is prompted for the suspected counterfeit detected. Or the extracted code value to be detected does not find the same original code value at the server, and then the user is prompted to detect suspected counterfeits.

Step S903, when the extracted code value to be detected is stored in the server, acquiring a dynamic encryption parameter corresponding to the code value to be detected, an original pattern anti-counterfeiting feature fingerprint corresponding to the code value to be detected and an N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch from the server;

step S904, processing the code value to be detected by using the dynamic encryption algorithm and the dynamic encryption parameter corresponding to the code value to be detected to obtain an embedded password of the anti-counterfeiting feature of the graph to be detected;

the processing manner of this step is similar to that of step S102, and is not described herein again.

Step S905, according to the graph anti-counterfeiting feature embedding password to be detected and the graph anti-counterfeiting feature extraction algorithm, obtaining a graph anti-counterfeiting feature fingerprint to be detected of the random additional point graph security code physical mark to be detected;

as shown in fig. 10, the pattern anti-counterfeit feature fingerprint to be detected can be obtained through the following steps S1001-S1006, and the original pattern anti-counterfeit feature fingerprint described above can also be obtained in a similar manner.

Step S1001, comparing the graph anti-counterfeiting feature embedding password to be detected with an original graph anti-counterfeiting feature embedding password corresponding to the code value to be detected, and writing a comparison result into the graph anti-counterfeiting feature fingerprint to be detected;

step S1002, verifying the contour length of the graphic anti-counterfeiting feature of the random additional point graphic security code real object identifier to be detected, and obtaining a first verification result;

wherein, divide the code point into two sets: the code points with the embedded pattern anti-counterfeiting features and the code points without the embedded pattern anti-counterfeiting features. And respectively calculating to obtain the theoretical image contour length Lt of each code point. And then obtaining contour information of each code point position on the random additional point pattern safety code real object mark to be detected, and calculating to obtain the detection contour length Lr of each code point position of the random additional point pattern safety code real object mark to be detected. And calculating the Mean Square Error (MSE) of the theoretical image contour length Lt and the detection contour length Lr of the two groups of code points and recording the MSE as Ey and En respectively. And calculating to obtain a weighted sum of two mean square error values by adopting the code point profile verification parameter weight wy of the embedded pattern anti-counterfeiting feature and the code point profile verification parameter weight wn of the non-embedded pattern anti-counterfeiting feature, wherein Ea = Ey wy + En dwn. A first verification result is obtained.

Step S1003, verifying whether the area of the graph anti-counterfeiting feature of the random additional point graph security code object identifier to be detected is hit, and obtaining a second verification result;

wherein, for one code point (if there is embedded graph, it contains embedded graph part), calculating to obtain array St of all point position coordinate value pairs (xt, yt). And then calculating an array Sr of position coordinate numerical value pairs (xr, yr) of all points contained in the graph corresponding to the code points (the embedded graph part is contained if the embedded graph exists) at the positions of the code points on the random additional point graph security code object identifier to be detected. And recording an area hit verification parameter initial value Ms as 0, calculating the matching rate of position coordinate value pairs in St and Sr, if the matching rate is greater than a preset area local hit threshold value of the embedded graph, successfully matching the code point and adding 1 to the Ms, otherwise, subtracting 1 from the Ms. And after all code points are detected and matched, a second verification result is obtained.

Step S1004, verifying the corner points of the graphic anti-counterfeiting feature of the graphic security code real object identifier of the random additional points to be detected, and obtaining a third verification result;

aiming at one code point embedded with the graphic anti-counterfeiting feature, the angular point position coordinate of the code point theory embedded with the graphic anti-counterfeiting feature and the gradient direction of the angular point are obtained according to the information such as the position of the code point embedded with the graphic anti-counterfeiting feature. Initializing a corner point verification parameter Ma of the embedded graph anti-counterfeiting feature to be 0, judging whether the corner point exists at a corner point position coordinate corresponding to a random additional point graph security code object identifier to be detected, if so, further judging whether the gradient direction at the corner point meets a preset direction judgment error threshold value requirement, if so, adding 1 to the Ma, otherwise, subtracting 1 from the Ma. And detecting whether the code points meet the threshold requirement or not to obtain a third verification result.

Step S1005, obtaining comparison results according to the first verification result, the second verification result, the third verification result and the respective threshold values, and writing the comparison results into the anti-counterfeiting characteristic fingerprint of the graph to be detected;

and obtaining different comparison results aiming at different relations between an array consisting of the first verification result, the second verification result and the third verification result and a threshold value, wherein the comparison results can be represented by characters and written in the anti-counterfeiting characteristic fingerprint of the graph to be detected.

And step S1006, outputting the anti-counterfeiting characteristic fingerprint of the graph to be detected.

And finally, outputting the fingerprint to obtain the fingerprint of the anti-counterfeiting characteristic of the graph to be detected.

Step S906, comparing the anti-counterfeiting characteristic fingerprint of the graph to be detected with the anti-counterfeiting characteristic fingerprint of the original graph corresponding to the code value to be detected, and calculating the matching rate of two character strings in the same character set encoding mode to obtain a single-frame passing result;

step S907, when the number of the single-frame passing results is accumulated to N, calculating a multi-frame passing rate statistic value;

wherein, preferably, 3. Ltoreq. N.ltoreq.10. And calculating a multi-frame passing rate statistic value by taking the 'single-frame passing number p divided by N' as a formula. The statistics of the multi-frame judgment result is more accurate, and the probability of judging whether the genuine products are fake or the counterfeit printed products are true due to light, angle and jitter is reduced.

Step S908, when the multi-frame throughput rate statistic value is smaller than the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch, a counterfeit is prompted;

and step S909, when the multi-frame throughput rate statistic is greater than or equal to the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch, prompting the genuine products.

Fig. 11 is a flowchart of a method for dynamically adjusting a decision threshold according to an embodiment of the present invention. As shown in fig. 11, the method includes:

step S1101, acquiring M graphic anti-counterfeiting characteristic fingerprints of random additional point graphic security code real object identifications corresponding to the same original code value;

because the printing is a process that characteristic changes are necessarily generated randomly, fingerprints generated by a genuine product (an electronic file is printed to be an image of a printed matter real object acquired by a camera) are different from original fingerprints (an image of the electronic file), and the fingerprints are not 100% identical, but the difference is within a certain statistical threshold. But the counterfeits are necessarily far from the print after being reproduced. The two can be separated by setting the false-proof judgment threshold value of the anti-counterfeiting characteristic fingerprint of N frames. Therefore, in order to enable the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch to be more accurate, the invention carries out the step of dynamically adjusting the judgment threshold value. Namely, firstly, directly acquiring the printed M (for example, 100) graphic anti-counterfeiting characteristic fingerprints of the random additional dot graphic security code physical identifications corresponding to the same original code value.

Step S1102, comparing the graph anti-counterfeiting characteristic fingerprints of the random additional dot graph security code real object identifications corresponding to M identical original code values with the original graph anti-counterfeiting characteristic fingerprints corresponding to the original code values to obtain an average value of M single-frame matching rates;

here, the single frame matching rate, that is, the abcd and abc3 matching rates, is 75%, for example. This embodiment only detects to M random additional point figure security code physical identification, has realized not needing to reform transform the cost of producing the line to manufacturing enterprise and has saved.

Step S1103, when the average value is smaller than the N-frame anti-counterfeit feature fingerprint authenticity judgment threshold value corresponding to the current printing batch, updating the N-frame anti-counterfeit feature fingerprint authenticity judgment threshold value corresponding to the current printing batch to the average value to the server.

Because the risk that the printed product deviates from the preset multi-frame passing rate due to the printing deviation of the pattern anti-counterfeiting features of different printing batches caused by the printing randomness exists all the time, the passing rate quality inspection of the good product of the whole printing batch is realized at extremely low cost and efficiency after the calibration by the embodiment.

Fig. 12 is a schematic structural diagram of a random additional point anti-counterfeiting device based on a micro-point code according to an embodiment of the present invention. As shown in fig. 12, the apparatus includes: the system comprises a code map generating module 1, a password acquiring module 2, a document acquiring module 3, a parameter storage module 4, an identification processing module 5 and a parameter adjusting module 6, wherein the code map generating module 1 is used for generating a dot matrix code map by using any original code value based on the code system of a micro-point code; the password acquisition module 2 is used for processing the original code value by using a dynamic encryption algorithm and a dynamic encryption parameter corresponding to the original code value to obtain an original graphic anti-counterfeiting feature embedded password; the document acquisition module 3 is configured to: determining code point row numbers, code point column numbers, embedding directions, embedding offsets and the number of pixels added outwards relative to the center of code points of a plurality of graph anti-counterfeiting features embedded into the dot matrix code graph according to the original graph anti-counterfeiting feature embedded password and a graph anti-counterfeiting feature embedding algorithm; embedding the plurality of graphic anti-counterfeiting features into the dot matrix code image according to the code point row number, the code point column number, the embedding direction, the embedding offset and the number of the pixels added outwards from the center of the relative code point to obtain a random additional point graphic security code electronic document; the parameter storage module 4 is configured to store a dynamic encryption parameter corresponding to the original code value, an original pattern anti-counterfeiting feature fingerprint corresponding to the original code value, and an N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch to a server, where the original pattern anti-counterfeiting feature fingerprint is obtained by processing the random additional point pattern security code electronic document using the original pattern anti-counterfeiting feature embedded password and a pattern anti-counterfeiting feature extraction algorithm corresponding to the pattern anti-counterfeiting feature embedded algorithm; the mark processing module 5 is configured to print the random additional dot pattern security code electronic document into a random additional dot pattern security code physical mark, so as to detect the random additional dot pattern security code physical mark to be detected according to the dynamic encryption parameter corresponding to the original code value, the original pattern anti-counterfeiting feature fingerprint corresponding to the original code value, and the N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold corresponding to the current printing batch, so as to judge authenticity.

Preferably, the password obtaining module 2 is configured to: based on a linear congruence method, executing n times of random number generation operation to obtain an original graph anti-counterfeiting feature embedded password prototype; intercepting and splitting the anti-counterfeiting feature of the original graph embedded password prototype into 5 character strings; respectively carrying out MD5 encryption on the 5 character strings to obtain 5 encrypted character strings; and respectively taking the front 4 bits or the rear 4 bits of the 5 encrypted character strings to generate 5 arrays with the length of 4, and combining the arrays to obtain the original graph anti-counterfeiting feature embedded password.

Preferably, the document acquiring module 3 is configured to: the 1 st bit to the 4 th bit of the original graph anti-counterfeiting feature embedded password is converted into a first digital array through ASCII coding; taking the first 4 or the last 4 numbers of the first digital array, setting the odd number in each number as 1 and the even number as 0, and generating a first binary number with 4 bits; converting the first binary digits into decimal digits to obtain code point row numbers of a plurality of graph anti-counterfeiting features embedded into the dot matrix code graph; converting the 5 th bit to the 8 th bit of the original graph anti-counterfeiting feature embedded password into a second digital array through ASCII coding; taking the first 4 or the last 4 numbers of the second digital array, setting the odd number in each number as 1 and the even number as 0, and generating a second binary digit with 4 bits; converting the second binary digits into decimal digits to obtain code point sequence numbers of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code graph; converting the 9 th bit to the 12 th bit of the original graph anti-counterfeiting feature embedded password into a third digital array through ASCII coding; taking the front 4 or the back 4 numbers of the third digital array, setting the odd number in each number as 1 and the even number as 0, and generating a 4-bit third binary digit; converting the third binary digit into a decimal digit, dividing the decimal digit by 2, rounding, and adding 1 to obtain a first integer; determining the embedding directions of a plurality of graphic anti-counterfeiting features embedded into the dot matrix code pattern according to the first integer; converting the 13 th bit to the 16 th bit of the original graph anti-counterfeiting feature embedded password into a fourth digital array by ASCII coding; taking the first 4 or the last 4 numbers of the fourth digital array, setting the odd number in each number as 1 and the even number as 0, and generating a fourth binary digit with 4 bits; converting the fourth binary digit into a decimal digit, dividing the decimal digit by 4, and rounding down to obtain a second integer; determining the embedded offset of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code pattern according to the second integer; the 17 th to 20 th bits of the original graph anti-counterfeiting feature embedded password are converted into a fifth digital array through ASCII coding; taking the first 4 or the last 4 numbers of the fifth digital array, setting the odd number in each number as 1 and the even number as 0, and generating a fifth binary digit with 4 bits; converting the fifth binary digit into a decimal digit, dividing the decimal digit by 2, rounding down, and adding 1 to obtain a third integer; and determining the number of the pixels added outwards relative to the code point center of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code graph according to the third integer.

Preferably, the identification processing module 5 is configured to: extracting a code value to be detected of the random additional dot pattern security code real object identifier to be detected; when the extraction is unsuccessful within the preset time or the extracted code value to be detected is not stored in the server, a counterfeit product is prompted; when the extracted code value to be detected is stored in the server, acquiring a dynamic encryption parameter corresponding to the code value to be detected, an original graph anti-counterfeiting feature fingerprint corresponding to the code value to be detected and an N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch from the server; processing the code value to be detected by using the dynamic encryption algorithm and the dynamic encryption parameter corresponding to the code value to be detected to obtain an embedded password of the anti-counterfeiting characteristic of the graph to be detected; according to the graph anti-counterfeiting feature embedding password to be detected and the graph anti-counterfeiting feature extraction algorithm, obtaining a graph anti-counterfeiting feature fingerprint to be detected of the randomly attached dot-graph security code physical identification to be detected; comparing the graph anti-counterfeiting characteristic fingerprint to be detected with an original graph anti-counterfeiting characteristic fingerprint corresponding to the code value to be detected, and calculating the matching rate of two character strings in the same character set encoding mode to obtain a single-frame passing result; when the number of the single-frame passing results is accumulated to N, calculating a multi-frame passing rate statistic value; when the multi-frame throughput rate statistic value is smaller than the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch, prompting a counterfeit product; and prompting the genuine product when the multi-frame passing rate statistic value is greater than or equal to the authenticity judgment threshold value of the N frames of anti-counterfeiting feature fingerprints corresponding to the current printing batch.

Preferably, the apparatus further comprises a parameter adjustment module 6 for: acquiring graph anti-counterfeiting characteristic fingerprints of M random additional point graph security code real object identifications corresponding to the same original code value; comparing the graph anti-counterfeiting feature fingerprints of the random additional point graph security code real object identification corresponding to M identical original code values with the original graph anti-counterfeiting feature fingerprints corresponding to the original code values to obtain an average value of M single-frame matching rates; and when the average value is smaller than the N frames of anti-counterfeiting feature fingerprint authenticity judgment threshold values corresponding to the current printing batch, updating the N frames of anti-counterfeiting feature fingerprint authenticity judgment threshold values corresponding to the current printing batch to the average value and sending the average value to the server.

Preferably, the identification processing module 5 is configured to: comparing the graph anti-counterfeiting feature embedding password to be detected with an original graph anti-counterfeiting feature embedding password corresponding to the code value to be detected, and writing a comparison result into the graph anti-counterfeiting feature fingerprint to be detected; verifying the contour length of the graphic anti-counterfeiting feature of the random additional point graphic security code real object identifier to be detected, and obtaining a first verification result; verifying the area hit of the graph anti-counterfeiting feature of the random additional point graph security code physical identification to be detected, and obtaining a second verification result; verifying the corner points of the graph anti-counterfeiting characteristics of the random additional point graph security code real object identifier to be detected, and obtaining a third verification result; obtaining comparison results according to the first verification result, the second verification result, the third verification result and the respective threshold values, and writing the comparison results into the anti-counterfeiting characteristic fingerprint of the graph to be detected; and outputting the anti-counterfeiting characteristic fingerprint of the graph to be detected.

The above-mentioned embodiments of the random additional point anti-counterfeiting device based on the micro point code are similar to the above-mentioned embodiments of the random additional point anti-counterfeiting method based on the micro point code, and are not repeated herein.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.

The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A random additional point anti-counterfeiting method based on a micro-point code is characterized by comprising the following steps:

generating a dot matrix code image by using any original code value based on the code system of the micro-dot code;

processing the original code value by using a dynamic encryption algorithm and a dynamic encryption parameter corresponding to the original code value to obtain an original graph anti-counterfeiting feature embedded password;

determining code point row numbers, code point column numbers, embedding directions, embedding offsets and the number of pixels added outwards relative to the center of code points of a plurality of graph anti-counterfeiting features embedded into the dot matrix code graph according to the original graph anti-counterfeiting feature embedded password and a graph anti-counterfeiting feature embedding algorithm;

embedding the plurality of graphic anti-counterfeiting features into the dot matrix code image according to the code point row number, the code point column number, the embedding direction, the embedding offset and the number of the pixels added outwards from the center of the relative code point to obtain a random additional point graphic security code electronic document;

storing a dynamic encryption parameter corresponding to the original code value, an original graph anti-counterfeiting feature fingerprint corresponding to the original code value and an N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch to a server, wherein the original graph anti-counterfeiting feature fingerprint is obtained by processing the random additional point graph security code electronic document by using the original graph anti-counterfeiting feature embedded password and a graph anti-counterfeiting feature extraction algorithm corresponding to the graph anti-counterfeiting feature embedded algorithm;

and printing the random additional point pattern security code electronic document into a random additional point pattern security code real object identifier so as to detect the random additional point pattern security code real object identifier to be detected according to the dynamic encryption parameter corresponding to the original code value, the original pattern anti-counterfeiting feature fingerprint corresponding to the original code value and the N frames of anti-counterfeiting feature fingerprint authenticity judgment threshold values corresponding to the current printing batch so as to judge authenticity.

2. The random additional point anti-counterfeiting method based on the micro-point code according to claim 1, wherein the step of processing the original code value by using a dynamic encryption algorithm and a dynamic encryption parameter corresponding to the original code value to obtain an original graphic anti-counterfeiting feature embedded password comprises the following steps:

based on a linear congruence method, executing n times of random number generation operation to obtain an original graph anti-counterfeiting feature embedded password prototype;

intercepting and splitting the anti-counterfeiting feature of the original graph embedded password prototype into 5 character strings;

respectively carrying out MD5 encryption on the 5 character strings to obtain 5 encrypted character strings;

and respectively taking the front 4 bits or the rear 4 bits of the 5 encrypted character strings to generate 5 arrays with the length of 4, and combining the arrays to obtain the original graph anti-counterfeiting feature embedded password.

3. The random additional point anti-counterfeiting method based on the micro-point code according to claim 1, wherein the determining of the code point row number, the code point column number, the embedding direction, the embedding offset and the number of the pixels added outwards relative to the code point center of the plurality of graphic anti-counterfeiting features embedded in the dot code pattern according to the original graphic anti-counterfeiting feature embedded password and the graphic anti-counterfeiting feature embedding algorithm comprises:

converting the 1 st to 4 th bits of the original graph anti-counterfeiting feature embedded password into a first digital array through ASCII (American standard code for information interchange) coding;

taking the first 4 or the last 4 numbers of the first digital array, setting the odd number in each number as 1 and the even number as 0, and generating a first binary number with 4 bits;

converting the first binary digits into decimal digits to obtain code point row numbers of a plurality of graph anti-counterfeiting features embedded into the dot matrix code graph;

the 5 th bit to the 8 th bit of the original graph anti-counterfeiting feature embedded password is converted into a second digital array through ASCII coding;

taking the first 4 or the last 4 numbers of the second digital array, setting the odd number in each number as 1 and the even number as 0, and generating a second binary digit with 4 bits;

converting the second binary digits into decimal digits to obtain code point sequence numbers of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code graph;

converting the 9 th bit to the 12 th bit of the original graph anti-counterfeiting feature embedded password into a third digital array through ASCII coding;

taking the first 4 or the last 4 numbers of the third digital array, setting the odd number in each number as 1 and the even number as 0, and generating a 4-bit third binary digit;

converting the third binary digit into a decimal digit, dividing the decimal digit by 2, rounding, and adding 1 to obtain a first integer;

determining the embedding directions of a plurality of graphic anti-counterfeiting features embedded into the dot matrix code pattern according to the first integer;

converting 13 th to 16 th bits of the original graph anti-counterfeiting feature embedded password into a fourth digital array through ASCII (American standard code for information interchange) coding;

taking the first 4 or the last 4 numbers of the fourth digital array, setting the odd number in each number as 1 and the even number as 0, and generating a fourth binary digit with 4 bits;

converting the fourth binary digit into a decimal digit, dividing the decimal digit by 4, and rounding downwards to obtain a second integer;

determining the embedded offset of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code pattern according to the second integer;

the 17 th to 20 th bits of the original graph anti-counterfeiting feature embedded password are converted into a fifth digital array through ASCII coding;

taking the first 4 or the last 4 numbers of the fifth digital array, setting the odd number in each number as 1 and the even number as 0, and generating a fifth binary digit with 4 bits;

converting the fifth binary digit into a decimal digit, dividing the decimal digit by 2, rounding, and adding 1 to obtain a third integer;

and determining the number of the pixels added outwards relative to the code point center of the anti-counterfeiting features of the plurality of graphs embedded into the dot matrix code graph according to the third integer.

4. The random additional point anti-counterfeiting method based on the micro-point code as claimed in claim 1, wherein the step of detecting the physical mark of the random additional point pattern security code to be detected according to the dynamic encryption parameter corresponding to the original code value, the original pattern anti-counterfeiting feature fingerprint corresponding to the original code value and the authenticity judgment threshold of the N frames of anti-counterfeiting feature fingerprints corresponding to the current printing batch to judge authenticity comprises the following steps:

extracting a code value to be detected of the random additional dot pattern security code real object identifier to be detected;

when the extraction is unsuccessful within the preset time or the extracted code value to be detected is not stored in the server, a counterfeit product is prompted;

when the extracted code value to be detected is stored in the server, acquiring a dynamic encryption parameter corresponding to the code value to be detected, an original graph anti-counterfeiting feature fingerprint corresponding to the code value to be detected and an N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch from the server;

processing the code value to be detected by using the dynamic encryption algorithm and the dynamic encryption parameter corresponding to the code value to be detected to obtain an embedded password of the anti-counterfeiting feature of the graph to be detected;

according to the pattern anti-counterfeiting feature embedding password to be detected and the pattern anti-counterfeiting feature extraction algorithm, obtaining a pattern anti-counterfeiting feature fingerprint to be detected of the random additional point pattern security code real object identifier to be detected;

comparing the graph anti-counterfeiting characteristic fingerprint to be detected with an original graph anti-counterfeiting characteristic fingerprint corresponding to the code value to be detected, and calculating the matching rate of two character strings in the same character set encoding mode to obtain a single-frame passing result;

when the number of the single-frame passing results is accumulated to N, calculating a multi-frame passing rate statistic value;

when the multi-frame passing rate statistic value is smaller than the authenticity judgment threshold value of the N frames of anti-counterfeiting feature fingerprints corresponding to the current printing batch, prompting a counterfeit product;

and prompting the genuine product when the multi-frame passing rate statistic value is greater than or equal to the authenticity judgment threshold value of the N frames of anti-counterfeiting feature fingerprints corresponding to the current printing batch.

5. The random additive point anti-counterfeiting method based on the micro-point code is characterized by further comprising the following steps:

acquiring graph anti-counterfeiting characteristic fingerprints of M random additional point graph security code real object identifications corresponding to the same original code value;

comparing the graph anti-counterfeiting characteristic fingerprints of the random additional dot-graph security code real object identifications corresponding to M identical original code values with the original graph anti-counterfeiting characteristic fingerprints corresponding to the original code values to obtain an average value of M single-frame matching rates;

and when the average value is smaller than the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch, updating the authenticity judgment threshold value of the N frames of anti-counterfeiting characteristic fingerprints corresponding to the current printing batch as the average value to the server.

6. The random additional point anti-counterfeiting method based on the micro-point code as claimed in claim 4, wherein the step of obtaining the fingerprint of the to-be-detected pattern anti-counterfeiting feature of the to-be-detected random additional point pattern security code physical mark according to the to-be-detected pattern anti-counterfeiting feature embedded password and the pattern anti-counterfeiting feature extraction algorithm comprises:

comparing the graph anti-counterfeiting feature embedding password to be detected with an original graph anti-counterfeiting feature embedding password corresponding to the code value to be detected, and writing a comparison result into the graph anti-counterfeiting feature fingerprint to be detected;

verifying the contour length of the graphic anti-counterfeiting feature of the random additional point graphic security code real object identifier to be detected, and obtaining a first verification result;

verifying the area hit of the graph anti-counterfeiting feature of the random additional point graph security code physical identification to be detected, and obtaining a second verification result;

verifying the corner points of the graph anti-counterfeiting characteristics of the random additional point graph security code real object identifier to be detected, and obtaining a third verification result;

obtaining comparison results according to the first verification result, the second verification result, the third verification result and the respective threshold values, and writing the comparison results into the anti-counterfeiting characteristic fingerprint of the graph to be detected;

and outputting the anti-counterfeiting characteristic fingerprint of the graph to be detected.

7. The random additional point anti-counterfeiting method based on the micro point code as claimed in claim 1, wherein the code value can be a character string encoded by any character, when the code value of the micro point code is converted into binary, the data has an obvious gap of more than or equal to 1 data position, the physical mark of the random additional point graphic security code made by the micro point code has at least 90% robustness in the area of 20mm x 20mm, can be decoded in the contaminated area to any residual 3mm complete area, and can be read under the interference graphics except linear, bulk and special-shaped code points.

8. A random additional point anti-counterfeiting device based on a micro-point code is characterized by comprising:

a code pattern generating module, a password acquiring module, a document acquiring module, a parameter storing module and an identification processing module, wherein,

the code map generation module is used for generating a dot matrix code map by using any original code value based on the code system of the micro-dot code;

the password acquisition module is used for processing the original code value by using a dynamic encryption algorithm and a dynamic encryption parameter corresponding to the original code value to obtain an original graph anti-counterfeiting feature embedded password;

the document acquisition module is used for:

the parameter storage module is used for storing a dynamic encryption parameter corresponding to the original code value, an original graph anti-counterfeiting feature fingerprint corresponding to the original code value and an N-frame anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch to a server, wherein the original graph anti-counterfeiting feature fingerprint is obtained by processing the random additional point graph security code electronic document by using the original graph anti-counterfeiting feature embedded password and a graph anti-counterfeiting feature extraction algorithm corresponding to the graph anti-counterfeiting feature embedded algorithm;

the mark processing module is used for printing the random additional point pattern security code electronic document into a random additional point pattern security code real object mark so as to detect the random additional point pattern security code real object mark to be detected according to the dynamic encryption parameter corresponding to the original code value, the original pattern anti-counterfeiting feature fingerprint corresponding to the original code value and the N frames of anti-counterfeiting feature fingerprint authenticity judgment threshold value corresponding to the current printing batch so as to judge authenticity.

9. The random append point anti-counterfeiting device based on the micro-point code according to claim 8, wherein the password obtaining module is configured to:

10. The random additional point anti-counterfeiting device based on the micro-point code according to claim 8, wherein the document acquisition module is used for:

the 1 st bit to the 4 th bit of the original graph anti-counterfeiting feature embedded password is converted into a first digital array through ASCII coding;

converting the third binary digit into a decimal digit, dividing the decimal digit by 2, rounding down, and adding 1 to obtain a first integer;

converting the fourth binary digit into a decimal digit, dividing the decimal digit by 4, and rounding down to obtain a second integer;

11. The random additive point anti-counterfeiting device based on the micro-point code according to claim 8, wherein the identification processing module is used for:

comparing the anti-counterfeiting characteristic fingerprint of the graph to be detected with the anti-counterfeiting characteristic fingerprint of the original graph corresponding to the code value to be detected, and calculating the matching rate of two character strings in the same character set encoding mode to obtain a single-frame passing result;

12. The random additional point anti-counterfeiting device based on the micro-point code according to claim 8, characterized by further comprising a parameter adjusting module for:

comparing the graph anti-counterfeiting feature fingerprints of the random additional point graph security code real object identification corresponding to M identical original code values with the original graph anti-counterfeiting feature fingerprints corresponding to the original code values to obtain an average value of M single-frame matching rates;

and when the average value is smaller than the N frames of anti-counterfeiting feature fingerprint authenticity judgment threshold values corresponding to the current printing batch, updating the N frames of anti-counterfeiting feature fingerprint authenticity judgment threshold values corresponding to the current printing batch to the average value and sending the average value to the server.

13. The random additive point anti-counterfeiting device based on the micro-point code according to claim 11, wherein the identification processing module is configured to: